Technical Reports - Query Results

Pre-Pruning and Post-Pruning are two standard methods of dealing with
noise in concept learning. Pre-Pruning methods are very efficient,
while Post-Pruning methods typically are more accurate, but much
slower, because they have to generate an overly specific concept
description first. We have experimented with a variety of pruning
methods, including two new methods that try to combine and integrate
pre- and post-pruning in order to achieve both accuracy and
efficiency. This is verified with test series in a chess position
classification task.